NewsRel Uses Machine Learning To Summarize News Stories And Put Them On A Map

After 24 hours of staring at their screens, the teams that participated in our Disrupt NY 2013 Hackathon have now finished their projects and are currently presenting them onstage. With more than 160 hacks, there are far too many cool ones to write about, but one that stood out to me was NewsRel, an iPad-based news app that uses machine-learning techniques to understand how news stories relate to one other. The app uses Google Maps as its main interface and automatically decides which location is most appropriate for any given story.

The app currently uses Reuters‘ RSS feed and analyzes the stories, looking for clusters of related stories and then puts them on the map. Say you are looking at a story about the Boston Marathon bombings. The app, of course, will show you a number of news stories about it clustered around Boston, then maybe something about the president’s comments about it from Washington and another article that relates it to the massacre during the Munich Olympics in 1972.

In addition to this, the team built an algorithm that picks the most important sentences from each story to summarize it for you.

As you scroll through the stories, the app always recalculates the related stories on the fly, too, which makes for a pretty interesting news-reading experience. Besides the map, the team also decided to develop the user interface around gestures, so you swipe down to read the full story on the news service’s webpage and you can swipe left and right to scroll from one story to the next

The team members have a background in machine learning and iOS engineering. They met during their undergrad studies a few years ago and decided to team up for the hackathon. They told me that they plan to keep working on the app and release it in the near future.